In the following exercises, you will work on your own ‘research question’ using the GESIS Panel data. You can load the data first using my script (maybe it’s useful for you in the following exercises):
library(haven)
library(dplyr)
library(sjlabelled)
gp_covid <-
read_sav(
"./data/ZA5667_v1-1-0.sav"
) %>%
set_na(na = c(-1:-99, 97, 98)) %>%
rowwise() %>%
mutate(
mean_trust =
mean(
c_across(hzcy044a:hzcy052a),
na.rm = TRUE
)
) %>%
ungroup() %>%
remove_all_labels() %>%
mutate(
pol_leaning_cat =
case_when(
between(political_orientation, 0, 3) ~ "left",
between(political_orientation, 4, 7) ~ "center",
political_orientation > 7 ~ "right"
) %>%
as.factor()
) %>%
filter(pol_leaning_cat != "NA")
If you’re really struggling finding a proper pair, what about:
education_cat as covariate If it is part of your variables take any other…). Then check visually if the residuals are normally distributed.
performance and see package.
check_model() command.